In certain fields of endeavors such as the medical fields, but also others such as geology or nondestructive material testing, there is a reliance on image data. For instance, in medical imaging, such as CT (computed tomography), X-ray projection data (measured by a detector of an imager apparatus) are reconstructed to “image slices” of a volume by a reconstruction algorithm. Such slice images can be used to show, when displayed, the internal anatomy of a patient in a grayscale visualization. In this case, the image information is in the form of (in generally) different attenuation values that the X-ray experienced in its passage through the patient's body. Unfortunately there is oftentimes uncertainty in said image information caused by prevalent noise signals. These noise signals may stem from the measurement process at the detector or may stem from the reconstruction algorithm itself. Previously, the prevalence of noise has been mainly thought of as a nuisance that needs to be eliminated or has been ignored altogether.